Remote | £35,000-£40,000 pa equivalent depending on experience | full-time | 3 months fixed-term
Please send your CV to hello@ecosytravel.co.uk, with a covering letter setting out why you’re interested in the role and how you meet our criteria. You need the right to work in the UK for this role.
Who we are
Ecosy Travel is a tech for good company that’s revolutionising the way we travel. We’re developing innovative SaaS products to help travel businesses serve the growing demand for green travel, and transparent reporting of sustainability credentials. Ecosy makes it easy for everyone to find, book and share their eco escapes. We’re using novel data analytics to remove barriers to going green and support our customers to deliver a positive impact through their businesses.
We’re a growing team of remote workers, championing the benefits of the digital nomad lifestyle. We’re passionate about people, places and planet and are committed to utilising technology in novel ways to accelerate the transition to a regenerative tourism industry. We meet monthly and work together in-person whenever we’re in the same city.
Ecosy Travel is a certified social enterprise and pending B Corp dedicated to reducing the climate impact of travel & tourism. That means the majority of our profits will be reinvested in our social mission to cut greenhouse gas emissions in the travel & tourism sector. As a social enterprise we are also committed to creating an inclusive and supportive work culture that reflects our passion for a just transition to a green economy.
The role
Our data scientist will lead Ecosy’s work to develop carbon-optimisation algorithms, across our software components. They will conduct development work as part of our current Innovate UK funded project to develop a novel recommendation engine, cost-optimising net zero pathways for our partner properties. The successful candidate will maintain and improve our carbon-optimised routing algorithm.
This is an exciting opportunity to join the team in the early days and, for the right candidate, grow with the company. We are offering a fixed term contract for 3 months to complete the current project work, with scope for the role to become permanent (dependent on ongoing funding). Salary is negotiable depending on experience, up to £40,000 pa. We are open to discussing flexible working including job shares and flexible patterns of work. This is a remote or hybrid role. The successful candidate will start the role by 29th July.
Who we’re looking for
Essential:
- Proficiency in using Python for data science, e.g. scikit-learn, NumPy, Pandas libraries
- Proven skills and experience developing computational algorithms to solve problems.
- To be adaptable, self-motivated and organised in situations where the brief is more general and a degree of independence is required.
- Experience using data from external sources via API.
- Commitment to using tech innovations to unlock today’s biggest society challenges, including the climate crisis.
- Experience with AWS, notably AWS Lambda and AWS API Gateway.
Desirable:
- Proven skills and experience conducting geospatial analysis.
- Proven skills and experience developing a route optimisation algorithm.
- Experience working with emissions data and carbon accounting methodologies.
- Interest or experience in web development.
- Ability to work effectively both independently and in a team.
- Experience with AWS SageMaker and AWS IAM.
- Experience with training machine learning models.
- Experience with developing CI/CD pipelines. Ideally with GitHub actions.
- Familiarity with dashboard building or data analytics.
We are a positive and supportive team and hope to provide the conditions for you to take pride in your work and deliver high quality results. We have high standards and your best work will be acknowledged and appreciated.
We are an equal opportunities employer. If you require any reasonable adjustments for accessibility during the application process, please get in touch. Demographic groups with lower representation in tech are less likely to apply if they do not meet all the requirements – we encourage you to apply even if your experience does not align completely with the skill set outlined.
